A major limitation of current treatments for cancer is the selection of appropriate active agents for a patient. It is common that sub-optimal chemotherapy is provided to a patient, resulting in unsuccessful treatment, including death, disease progression, unnecessary toxicity, and higher health care costs. Further, some patients respond better without chemotherapy, using, for example, neoadjuvant or adjuvant therapy with surgery.
Assays to individualize and optimize cancer treatment, such as chemoresponse assays, have been developed to predict the potential efficacy of chemotherapy agents for a given patient prior to their administration. However, use of such assays is not widespread due, in-part, to difficulties in interpreting the data in a clinically meaningful way. For example, many such assays are thought to be unsuitable for providing accurate estimations of patient survival with particular treatment regimens (see. e.g., Fruehauf et al., Endocrine-Related Cancer 9:171-182 (2002)).
Therefore, there remains a need for methods that are useful for evaluating cancer and related diseases. Specifically, there is a need for methods that can direct a healthcare provider's treatment plan with a cancer patient, based on knowledge of characteristics of a patient's tumor.